From the court we were asked whether it is possible to determine if an image has been made with a specific digital camera. This question has to be answered in child pornography cases, where evidence is needed that a certain picture has been made with a specific camera. We have looked into different methods of examining the cameras to determine if a specific image has been made with a camera: defects in CCDs, file formats that are used, noise introduced by the pixel arrays and watermarking in images used by the camera manufacturer.

In this paper, the importance of modern technology in forensic investigations is discussed. Recent technological developments are creating new possibilities to perform robust scientific measurements and studies outside the controlled laboratory environment. The benefits of real-time, on-site forensic investigations are manifold and such technology has the potential to strongly increase the speed and efficacy of the criminal justice system. However, such benefits are only realized when quality can be guaranteed at all times and findings can be used as forensic evidence in court. At the Netherlands Forensic Institute, innovation efforts are currently undertaken to develop integrated forensic platform solutions that allow for the forensic investigation of human biological traces, the chemical identification of illicit drugs and the study of large amounts of digital evidence. These platforms enable field investigations, yield robust and validated evidence and allow for forensic intelligence and targeted use of expert capacity at the forensic institutes. This technological revolution in forensic science could ultimately lead to a paradigm shift in which a new role of the forensic expert emerges as developer and custodian of integrated forensic platforms.

This article studies the application of models of OpenFace (an open-source deep learning algorithm) to forensics by using multiple datasets. The discussion focuses on the ability of the software to identify similarities and differences between faces based on images from forensics. Experiments using OpenFace on the Labeled Faces in the Wild (LFW)-raw dataset, the LFW-deep funnelled dataset, the Surveillance Cameras Face Database (SCface) and ForenFace datasets showed that as the resolution of the input images worsened, the effectiveness of the models degraded. In general, the effect of the quality of the query images on the efficiency of OpenFace was apparent. Therefore, OpenFace in its current form is inadequate for application to forensics, but can be improved to offer promising uses in the field.